Gender: Female 
Age: 35-44
Nationality: United Kingdom
Ethnicity: Other. Please specify mixed white/asian
Marital status: Married 
First language: English 
Religion: Muslim 
Education: Undergraduate degree
Mother's education: High school or below
Father's education: High school or below
Self-assessed socioeconomic status (1-10): 7
Home: Own 
Employment: Employed full time
Occupation: Professionals or highly skilled workers (those who increase the existing stock of knowledge or teach about it in a systematic manner, e.g. engineer, doctor, teacher, lawyer)
Mother's occupation: Clerical support workers (those who perform clerical duties such as organizing, storing, computing and retrieving information)
Father's occupation: Elementary occupations (jobs that involve simple and routine tasks which may require the use of hand-held tools and considerable physical effort)
Hobbies: Visit to stately homes;Go to museums and galleries;Do arts and crafts 
Devices used daily: Laptop;Smartphone;Tablet;Smartwatch 
NLP tools known: Spell checker (i.e., correcting misspellings);Grammar checker (i.e., correcting grammar mistakes);E-mail spam detection (i.e., automatically send spam e-mails to your Trash folder);Sentiment analysis (e.g. automatically detect if user reviews are positive or negative)Machine translation (e.g. translate Chinese or Russian into English, and vice versa);Paraphrasing and Summarisation (i.e., automatically produce alternative descriptions of written text);Question Answering & Search Engine. (e.g., browsers or ask questions to smart devices/assistants);Speech-to-Text (i.e. a computer transcribing your spoken language to written language);Text-to-Speech (i.e, computers being able to read out loud written language) 
NLP tools used: Spell checker (i.e., correcting misspellings);Grammar checker (i.e., correcting grammar mistakes);E-mail spam detection (i.e., automatically send spam e-mails to your Trash folder);Sentiment analysis (e.g. automatically detect if user reviews are positive or negative)Machine translation (e.g. translate Chinese or Russian into English, and vice versa);Paraphrasing and Summarisation (i.e., automatically produce alternative descriptions of written text);Text-to-Speech (i.e, computers being able to read out loud written language);Question Answering & Search Engine. (e.g., browsers or ask questions to smart devices/assistants) 
NLP tools they would find useful: Spell checker (i.e., correcting misspellings);Grammar checker (i.e., correcting grammar mistakes);E-mail spam detection (i.e., automatically send spam e-mails to your Trash folder);Sentiment analysis (e.g. automatically detect if user reviews are positive or negative)Machine translation (e.g. translate Chinese or Russian into English, and vice versa);Paraphrasing and Summarisation (i.e., automatically produce alternative descriptions of written text);Question Answering & Search Engine. (e.g., browsers or ask questions to smart devices/assistants);Speech-to-Text (i.e. a computer transcribing your spoken language to written language);Text-to-Speech (i.e, computers being able to read out loud written language);Reading text from scanned documents (i.e. “Optical character recognition” or OCR. Given an image representing printed text, determine the corresponding text.) 
Frequency of LLM use: Nearly every day
LLMs used: ChatGPT;GitHub Copilot;Google Gemini 
LLM use cases: Coding;Translation;Brainstorming;Generic chatbot conversation;Answering questions about general knowledge;Collecting references;Summarizing long texts 
Contexts of LLM use: Work;Learning;Personal;Technical 
Prompt 1: write a piece of python script that will split a large csv file into 10mb csv chunk files and write into a folder
Prompt 2: rewrite the below resume summary to make sense for a person wanting to to get a promotion within their current company [resume extract here]
Prompt 3: write a piece of python code that will review a document and only let it pass if the document has a certain character included
Prompt 4: rewrite the below python code to make it more efficient [code extract]
Prompt 5: rewrite the below sql query to condense it without changing the outcome
Prompt 6: rewrite the below email to sound more professional [email extract]
Prompt 7: write out an email intended for a manger to let them know in a professional way that they are requesting too many one to ones [email extract]
Prompt 8: make the above email shorter and less formal but still professional
Prompt 9: give me a short summary of the novel "The Kite Runner'
Prompt 10: What is the capital city of mongolia
Comments: survey was awkward to access on the phone so had to revert to desktop